This invention relates generally to x-ray methods and apparatus, and more particularly to methods and apparatus that provide for the classification of structures in a dataset.
Digital Tomosynthesis is widely used for three-dimensional (3D) reconstruction of objects acquired from limited angle x-ray projection imaging with a stationary digital detector. It is a refinement of conventional geometric tomography, which has been known since the 1930s. As with geometric tomography, tomosynthesis suffers from the residual blur of objects outside the plane of interest. This tomographic blur from overlying anatomy obscures detail in the plane of interest and limits the contrast enhancement of the slices. Removing the overlying blurred anatomic structures improves contrast of in-plane structures by restricting the dynamic range of the image to that of the section of interest, as well as by removing residual structures that may have frequency content similar to that of some objects of interest in that section. At a fundamental level, the point-spread function (PSF) of a tomosynthesis dataset characterizes the spread of blur in the imaging volume, and is shift-variant in nature. However, removing the complete blur is a non-trivial task. It is computationally intensive and because of the extent of the PSF, it is not easy to eliminate blur.